FUNOVA Preprocessing QC statistics ¶

January 2025¶

In [21]:
import os
NOVA_HOME = "/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA"
NOVA_DATA_HOME = '/home/labs/hornsteinlab/Collaboration/FUNOVA'

LOGS_PATH = os.path.join(NOVA_DATA_HOME, "outputs/preprocessing/logs/")
PLOT_PATH = os.path.join(NOVA_DATA_HOME, "outputs/logs/")

os.chdir(NOVA_HOME)

import pandas as pd
import numpy as np
import contextlib
import io
from IPython.display import display, Javascript
import seaborn as sns
from tools.preprocessing_tools.qc_reports.qc_utils import log_files_qc, run_validate_folder_structure, display_diff, sample_and_calc_variance, \
                                                show_site_survival_dapi_brenner, show_site_survival_dapi_cellpose, \
                                                show_site_survival_dapi_tiling, show_site_survival_target_brenner, \
                                                calc_total_sums, plot_filtering_heatmap, show_total_sum_tables, \
                                                plot_cell_count, plot_catplot, plot_hm_combine_batches, plot_hm, \
                                                run_calc_hist_new, plot_marker_data, find_bad_wells,\
                                                show_site_survival_by_brenner_on_dapi_tiles, show_site_survival_target_brenner_tiles
                                                
from tools.preprocessing_tools.qc_reports.qc_config import (
    funova_markers as markers,
    funova_cell_lines as cell_lines,
    funova_cell_lines_to_cond as cell_lines_to_cond,
    funova_cell_lines_for_disp as cell_lines_for_disp,
    funova_reps as reps,
    funova_line_colors as line_colors,
    funova_lines_order as lines_order,
    funova_custom_palette as custom_palette,
    funova_expected_dapi_raw as expected_dapi_raw,
    funova_panels as panels,
    funova_marker_info as marker_info
)

%load_ext autoreload
%autoreload 2

The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload
In [3]:
# choose batches
batches = ['Batch3', 'Batch4']#, 'batch2', 'batch3']
batches
Out[3]:
['Batch3', 'Batch4']

I have created a folder called 'Batch3' in the logs dir and put all files inside

In [4]:
validate_antibody = False
In [5]:
df = log_files_qc(LOGS_PATH, batches, only_wt_cond = False)

reading logs of Batch3

Total of 1 files were read.
Before dup handeling  (172504, 22)
After duplication removal #1: (172504, 23)
After duplication removal #2: (172504, 23)
In [6]:
df['filename'] = df['filename'].str.split('-').str[0]
df['site_num'] = df['site_num'].str.split('-').str[0]
In [7]:
df_dapi = df[df.marker=='DAPI']
df_target = df[df.marker!='DAPI']

Actual Files Validation¶

Raw Files Validation¶

  1. How many site tiff files do we have in each folder?
  2. Are all existing files valid? (tif, at least 2049kB, not corrupetd)
In [8]:
root_directory_raw = os.path.join(NOVA_DATA_HOME, 'input', 'images', 'raw')
In [9]:
# # Create the marker info dfs

# import os
# import pandas as pd

# # Define the root path
# root_path = "/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/raw/"

# # Initialize a dictionary to store the data
# data = {}

# # Walk through the directory structure
# for dirpath, dirnames, filenames in os.walk(root_path):
#     # Check if the current path contains 'repX' and a subfolder for the marker
#     if os.path.basename(os.path.dirname(dirpath)).startswith("rep"):  # Check for 'repX' in parent folder
#         if "Batch3" in dirpath or "Batch4" in dirpath:  # Check if the path contains "Batch3" or "Batch4"
#             marker = os.path.basename(dirpath)  # The marker is the current folder
#             panel_folder = os.path.basename(os.path.dirname(os.path.dirname(os.path.dirname(dirpath))))  # Three levels up for the panel
#             if panel_folder.lower().startswith("panel"):  # Ensure it's a panel folder
#                 panel = panel_folder.replace("panel", "").strip()

#                 # Add marker and panel information
#                 if marker not in data:
#                     data[marker] = {"Antibody": [], "panel": []}  # Initialize marker entry
#                 data[marker]["panel"].append(panel)  # Add panel to the marker

# # Convert the data to a DataFrame
# final_marker_info = pd.DataFrame.from_dict(data, orient="index")

# # Ensure 'panel' and 'Antibody' are arrays and unique panels
# final_marker_info["panel"] = final_marker_info["panel"].apply(lambda x: sorted(set(x)))  # Remove duplicates and sort
# final_marker_info["Antibody"] = [[] for _ in range(len(final_marker_info))]  # Ensure Antibody is an empty array
In [10]:
batches_raw = [batch.replace("_16bit_no_downsample","") for batch in batches]
raws = run_validate_folder_structure(root_directory_raw, False, panels, markers.copy(), PLOT_PATH, marker_info,
                                    cell_lines_to_cond, reps, cell_lines_for_disp, expected_dapi_raw,
                                     batches=batches_raw, fig_width=8,fig_height = 40,
                                    expected_count=100, validate_antibody = validate_antibody)

Batch3
Folder structure is valid.
No bad files are found.
Total Sites:  118400

========
Batch4
Folder structure is valid.
No bad files are found.
Total Sites:  118400

========
====================

Processed Files Validation¶

  1. How many site npy files do we have in each folder? -> How many sites survived the pre-processing?
  2. Are all existing files valid? (at least 100kB, npy not corrupted)
In [11]:
root_directory_proc = os.path.join(NOVA_DATA_HOME, 'input', 'images', 'processed')
procs = run_validate_folder_structure(root_directory_proc, True, panels, markers, PLOT_PATH, marker_info,
                                    cell_lines_to_cond, reps, cell_lines_for_disp, expected_dapi_raw,
                                     batches=batches, fig_width=8,fig_height = 40,
                                    expected_count=100, validate_antibody = validate_antibody)

Batch3
Folder structure is valid.
1152 files are bad:
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep1_r05c05f52-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep2_r05c06f07-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep2_r05c06f28-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep2_r05c06f08-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep2_r05c06f16-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep2_r05c06f14-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep1_r05c05f24-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep2_r05c06f92-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep1_r05c05f22-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep2_r05c06f03-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep1_r05c05f17-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep2_r05c06f06-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep1_r05c05f18-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep1_r05c05f29-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep1_r05c05f19-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF4, rep1_r05c05f65-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-ATF6, rep1_r05c05f80-ch2t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/UPR-IRE1a, rep1_r05c03f96-ch2t1_panelB_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/DNA-damage-P53BP1, rep1_r05c19f65-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/DNA-damage-P53BP1, rep2_r05c20f95-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/DNA-damage-P53BP1, rep2_r05c20f13-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/DNA-damage-P53BP1, rep1_r05c19f30-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/DNA-damage-P53BP1, rep2_r05c20f80-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/DNA-damage-P53BP1, rep2_r05c20f79-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/DNA-damage-P53BP1, rep2_r05c20f02-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/DNA-damage-P53BP1, rep1_r05c19f95-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-HMGB1, rep2_r05c18f64-ch2t1_panelI_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-HMGB1, rep1_r05c17f97-ch2t1_panelI_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-HMGB1, rep1_r05c17f81-ch2t1_panelI_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necrosis, rep1_r05c17f09-ch3t1_panelI_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Parthanatos-early, rep2_r05c16f64-ch3t1_panelH_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Parthanatos-early, rep2_r05c16f33-ch3t1_panelH_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Parthanatos-early, rep1_r05c15f80-ch3t1_panelH_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/TDP-43, rep2_r05c14f09-ch3t1_panelG_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/TDP-43, rep2_r05c14f84-ch3t1_panelG_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/TDP-43, rep2_r05c14f02-ch3t1_panelG_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/TDP-43, rep2_r05c14f89-ch3t1_panelG_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/TDP-43, rep2_r05c14f20-ch3t1_panelG_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/TDP-43, rep1_r05c13f34-ch3t1_panelG_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Splicing-factories, rep2_r05c12f03-ch2t1_panelF_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Splicing-factories, rep2_r05c12f65-ch2t1_panelF_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Aberrant-splicing, rep2_r05c10f97-ch3t1_panelE_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep1_r05c21f22-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep2_r05c22f49-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep2_r05c22f13-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep2_r05c22f94-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep2_r05c22f78-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep2_r05c22f11-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep2_r05c22f33-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep2_r05c22f45-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/Untreated/Necroptosis-pMLKL, rep2_r05c22f38-ch3t1_panelK_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep2_r13c06f89-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep1_r13c05f23-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep1_r13c05f20-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep1_r13c05f08-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep2_r13c06f79-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep1_r13c05f06-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep1_r13c05f05-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep1_r13c05f17-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep1_r13c05f49-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep1_r13c05f79-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF4, rep2_r13c06f64-ch3t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-ATF6, rep2_r13c06f64-ch2t1_panelC_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/UPR-IRE1a, rep1_r13c03f18-ch2t1_panelB_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/DNA-damage-P53BP1, rep1_r13c19f78-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/DNA-damage-P53BP1, rep1_r13c19f05-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/DNA-damage-P53BP1, rep2_r13c20f10-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/DNA-damage-P53BP1, rep1_r13c19f16-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/DNA-damage-P53BP1, rep1_r13c19f96-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/DNA-damage-P53BP1, rep2_r13c20f12-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/DNA-damage-P53BP1, rep2_r13c20f31-ch2t1_panelJ_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/Necroptosis-HMGB1, rep2_r13c18f51-ch2t1_panelI_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/Necroptosis-HMGB1, rep1_r13c17f82-ch2t1_panelI_Control-1001733_processed.npy small size (0.128 kB)
/home/labs/hornsteinlab/Collaboration/FUNOVA/input/images/processed/Batch3/Control-1001733/stress/Necroptosis-HMGB1, rep2_r13c18f84-ch2t1_panelI_Control-1001733_processed.npy small size (0.128 kB)
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Total Sites:  66390

========
Batch4
Folder structure is valid.
1382 files are bad:
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Total Sites:  79706

========
====================

Difference between Raw and Processed¶

In [12]:
display_diff(batches, raws, procs, PLOT_PATH, fig_width=8, fig_height = 40)

Batch3

========
Batch4

========

Variance in each batch (of processed files)¶

In [13]:
for batch in batches:
    with contextlib.redirect_stdout(io.StringIO()):
        var = sample_and_calc_variance(root_directory_proc, batch, 
                                       sample_size_per_markers=200, cond_count=1, rep_count=len(reps), 
                                       num_markers=len(markers))
    print(f'{batch} var: ',var)

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)

Batch3 var:  nan

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:29: RuntimeWarning: Mean of empty slice.
  tiles_var = np.var(x, axis=(1,2)).mean()
/home/labs/hornsteinlab/galavir/.conda/envs/nova/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide
  ret = ret.dtype.type(ret / rcount)

Batch4 var:  nan

Preprocessing Filtering qc¶

By order of filtering

1. % site survival after Brenner on DAPI channel¶

Percentage out of the total sites

In [14]:
dapi_filter_by_brenner = show_site_survival_dapi_brenner(df_dapi,batches, line_colors, panels,
                                                        figsize=(6,18), reps=reps, vmax=100)

2. % Site survival after Cellpose¶

Percentage out of the sites that passed the previous filter. In parenthesis are absolute values.

A site will be filtered out if Cellpose found 0 cells in it.

In [15]:
dapi_filter_by_cellpose = show_site_survival_dapi_cellpose(df_dapi, batches, dapi_filter_by_brenner, 
                                                           line_colors, panels, figsize=(6,18), reps=reps)

3. % Site survival by tiling¶

Percentage out of the sites that passed the previous filter. In parenthesis are absolute values.

A site will be filtered out if after tiling, no tile is containing at least 85% of a cell that Cellpose detected.

In [16]:
dapi_filter_by_tiling=show_site_survival_dapi_tiling(df_dapi, batches, dapi_filter_by_cellpose, 
                                                     line_colors, panels, figsize=(6,18), reps=reps)

4. % Site survival after Brenner on DAPI's tiles¶

Percentage out of the sites that passed the previous filter. In parenthesis are absolute values (if different than the percentages).

In [17]:
dapi_filter_by_brenner_tiles=show_site_survival_by_brenner_on_dapi_tiles(df_dapi, batches, dapi_filter_by_tiling, 
                                                     line_colors, panels, figsize=(6,18), reps=reps)

5. % Site survival after Brenner on target channel¶

Percentage out of the sites that passed the previous filter. In parenthesis are absolute values (if different than the percentages).

In [18]:
show_site_survival_target_brenner(df_dapi, df_target, dapi_filter_by_tiling,
                                 figsize=(6,24), markers=markers)
In [22]:
df_dapi.iloc[np.where(df_dapi['n_valid_tiles']-df_dapi['n_valid_tiles_after_tiles_brenner'])][['n_valid_tiles','n_valid_tiles_after_tiles_brenner']]
Out[22]:
n_valid_tiles n_valid_tiles_after_tiles_brenner
54254 1 0.0
54275 2 0.0
54274 1 0.0
54223 3 0.0
54293 1 0.0
... ... ...
111468 4 3.0
111383 1 0.0
111411 4 3.0
111650 1 0.0
111808 6 5.0

6425 rows × 2 columns

Find non valid wells

In [23]:
dfb = pd.read_csv("/home/labs/hornsteinlab/Collaboration/FUNOVA/outputs/preprocessing/brenner/raw_metrics280125_exp3.csv")
# Extract the panel (e.g., "panelD") from the Path column
dfb['Panel'] = dfb['Path'].str.extract(r'/panel([A-Z])/', expand=True)
find_bad_wells(dfb, threshold=10000, percentage_filter=60)
Out[23]:
CellLine Marker Count_table1 Count_table2 Percentage Combination Panel Condition Rep Batch
0 Control_1017118 Aberrant-splicing 580 800 72.50 ['CellLine', 'Marker'] NaN NaN NaN NaN
1 Control_1017118 Aberrant-splicing 580 800 72.50 ['Panel', 'CellLine', 'Marker'] E NaN NaN NaN
2 Control_1017118 Aberrant-splicing 318 400 79.50 ['Condition', 'CellLine', 'Marker'] NaN Untreated NaN NaN
3 Control_1017118 DNA-damage-pH2Ax 306 400 76.50 ['Condition', 'CellLine', 'Marker'] NaN Untreated NaN NaN
4 C9orf72-HRE_981344 DNA-damage-P53BP1 273 400 68.25 ['Condition', 'CellLine', 'Marker'] NaN stress NaN NaN
... ... ... ... ... ... ... ... ... ... ...
188 C9orf72-HRE_1008566 Senescence-signaling 98 100 98.00 ['Panel', 'Condition', 'CellLine', 'Rep', 'Bat... L stress rep1 Batch2
189 C9orf72-HRE_981344 DAPI 91 100 91.00 ['Panel', 'Condition', 'CellLine', 'Rep', 'Bat... L stress rep1 Batch2
190 C9orf72-HRE_981344 Protein-degradation 93 100 93.00 ['Panel', 'Condition', 'CellLine', 'Rep', 'Bat... L stress rep1 Batch2
191 C9orf72-HRE_981344 Senescence-signaling 93 100 93.00 ['Panel', 'Condition', 'CellLine', 'Rep', 'Bat... L stress rep1 Batch2
192 Control_1048087 Senescence-signaling 99 100 99.00 ['Panel', 'Condition', 'CellLine', 'Rep', 'Bat... L stress rep2 Batch1

193 rows × 10 columns

6. % Site survival after Brenner on target channel tiles¶

Percentage out of the tiles that passed the previous filter. In parenthesis are absolute values (if different than the percentages).

In [24]:
show_site_survival_target_brenner_tiles(df_dapi, df_target, dapi_filter_by_brenner_tiles,
                                 figsize=(6,24), markers=markers)

Statistics About the Processed Files¶

In [25]:
names = ['Total number of tiles', 'Total number of whole cells']
stats = ['n_valid_tiles_after_tiles_brenner','site_whole_cells_counts_sum','site_cell_count','site_cell_count_sum']
total_sum = calc_total_sums(df_target, df_dapi, stats, markers)
In [26]:
total_sum.rename(columns={'n_valid_tiles_after_tiles_brenner': 'n_valid_tiles'}, inplace=True)
In [27]:
plot_marker_data(total_sum, split_by_cell_line=True)

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(
In [28]:
plot_marker_data(total_sum, split_by_cell_line=False)

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1351: FutureWarning: 

The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.

  sns.barplot(

Total tiles¶

In [29]:
total_sum.n_valid_tiles.sum()
Out[29]:
642891.0

Total whole nuclei in tiles¶

In [30]:
total_sum[total_sum.marker =='DAPI'].site_whole_cells_counts_sum.sum()
Out[30]:
242511.0

Total nuclei in sites¶

In [31]:
total_sum[total_sum.marker =='DAPI'].site_cell_count.sum()
Out[31]:
701521.0
In [32]:
show_total_sum_tables(total_sum)
n_valid_tiles % valid tiles site_whole_cells_counts_sum site_cell_count
Batch3
count 1184.000000 1184.000000 1184.000000 1184.000000
mean 227.003378 2.270034 253.168919 745.046453
std 185.542179 1.855422 208.007482 648.425128
min 9.000000 0.090000 9.000000 19.000000
25% 84.000000 0.840000 96.750000 244.000000
50% 178.000000 1.780000 198.500000 565.000000
75% 323.250000 3.232500 355.250000 1054.000000
max 1023.000000 10.230000 1178.000000 3673.000000
sum 268772.000000 NaN 299752.000000 882135.000000
expected_count 450.000000 450.000000 450.000000 450.000000
n_valid_tiles % valid tiles site_whole_cells_counts_sum site_cell_count
Batch4
count 1184.000000 1184.000000 1184.000000 1.184000e+03
mean 315.978885 3.159789 349.445101 9.770076e+02
std 230.867914 2.308679 258.543836 7.640473e+02
min 10.000000 0.100000 10.000000 2.400000e+01
25% 133.750000 1.337500 148.000000 3.920000e+02
50% 252.000000 2.520000 278.000000 7.355000e+02
75% 450.000000 4.500000 498.500000 1.407250e+03
max 1072.000000 10.720000 1272.000000 3.604000e+03
sum 374119.000000 NaN 413743.000000 1.156777e+06
expected_count 450.000000 450.000000 450.000000 4.500000e+02
n valid tiles % valid tiles site_whole_cells_counts_sum site_cell_count
All batches
count 2368.000000 2368.000000 2368.000000 2.368000e+03
mean 271.491132 2.714911 301.307010 8.610270e+02
std 214.066373 2.140664 239.480707 7.178835e+02
min 9.000000 0.090000 9.000000 1.900000e+01
25% 104.750000 1.047500 117.000000 3.047500e+02
50% 218.000000 2.180000 238.000000 6.450000e+02
75% 382.000000 3.820000 417.250000 1.217250e+03
max 1072.000000 10.720000 1272.000000 3.673000e+03
sum 642891.000000 NaN 713495.000000 2.038912e+06
expected_count 450.000000 450.000000 450.000000 4.500000e+02

Show Total Tile Counts¶

For each batch, cell line, replicate and markerTotal number of tiles

In [33]:
to_heatmap = total_sum.rename(columns={'n_valid_tiles':'index'})
plot_filtering_heatmap(to_heatmap, extra_index='marker', vmin=None, vmax=None,
                      xlabel = 'Total number of tiles', show_sum=True, figsize=(6,24))

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:388: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax.set_yticklabels(ax.get_yticklabels(), fontsize=10)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:388: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax.set_yticklabels(ax.get_yticklabels(), fontsize=10)

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:388: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax.set_yticklabels(ax.get_yticklabels(), fontsize=10)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:388: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax.set_yticklabels(ax.get_yticklabels(), fontsize=10)

Show Total Whole Cell Counts¶

For each batch, cell line, replicate and markerTotal number of tiles

In [34]:
to_heatmap = total_sum.rename(columns={'site_whole_cells_counts_sum':'index'})
plot_filtering_heatmap(to_heatmap, extra_index='marker', vmin=None, vmax=None,
                      xlabel = 'Total number of whole cells', show_sum=True, figsize=(6,24))

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:388: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax.set_yticklabels(ax.get_yticklabels(), fontsize=10)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:388: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax.set_yticklabels(ax.get_yticklabels(), fontsize=10)

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:388: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax.set_yticklabels(ax.get_yticklabels(), fontsize=10)
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:388: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.
  ax.set_yticklabels(ax.get_yticklabels(), fontsize=10)

Show Cell Count Statistics per Batch¶

In [35]:
df_no_empty_sites = df_dapi[df_dapi.n_valid_tiles_after_tiles_brenner !=0]
plot_cell_count(df_no_empty_sites, lines_order, custom_palette, y='site_cell_count_sum', 
                title='Cell Count Average per Site (from tiles)', figsize=(16,6))

plot_cell_count(df_no_empty_sites, lines_order, custom_palette, y='site_whole_cells_counts_sum',
                title='Whole Cell Count Average per Site',figsize=(16,6))

plot_cell_count(df_no_empty_sites, lines_order, custom_palette, y='site_cell_count',
               title='Cellpose Cell Count Average per Site',figsize=(16,6))

Show Tiles per Site Statistics¶

In [36]:
df_dapi.groupby(['cell_line_cond']).n_valid_tiles_after_tiles_brenner.mean()
Out[36]:
cell_line_cond
C9orf72-HRE-1008566 Untreated      1.377811
C9orf72-HRE-1008566 stress         0.950359
C9orf72-HRE-981344 Untreated       4.198874
C9orf72-HRE-981344 stress          3.950221
Control-1001733 Untreated          0.868755
Control-1001733 stress             0.637314
Control-1017118 Untreated          3.947226
Control-1017118 stress             3.331172
Control-1025045 Untreated          7.347399
Control-1025045 stress             6.443509
Control-1048087 Untreated          1.981532
Control-1048087 stress             1.837889
TDP--43-G348V-1057052 Untreated    2.024302
TDP--43-G348V-1057052 stress       1.343456
TDP--43-N390D-1005373 Untreated    2.836432
TDP--43-N390D-1005373 stress       2.163921
Name: n_valid_tiles_after_tiles_brenner, dtype: float64
In [37]:
plot_catplot(df_dapi, sns.color_palette('colorblind'), reps=reps,x='cell_line', y_title='Valid Tiles Count', x_title='Cell Line', y='n_valid_tiles_after_tiles_brenner', hue='rep',
             height=4, aspect=2)

/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1028: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  df.loc[:, 'batch_rep'] = df['batch'] + " " + df['rep']
/home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/tools/preprocessing_tools/qc_reports/qc_utils.py:1039: UserWarning: The palette list has more values (10) than needed (2), which may not be intended.
  g = sns.catplot(kind='box', data=df, y=y, x=x,height=height, aspect=aspect, hue=hue, palette=palette,

Show Mean of cell count in valid tiles¶

In [38]:
# plot_hm(df_dapi, split_by='rep', rows='cell_line', columns='panel', vmax=3)

Assessing Staining Reproducibility and Outliers¶

In [ ]:
# for batch in batches:
#     print(batch)
#     run_calc_hist_new(batch,cell_lines_for_disp, markers, root_directory_raw, root_directory_proc,
#                            hist_sample=10,sample_size_per_markers=10, ncols=4, nrows=1, figsize=(6,2))
#     print("="*30)
In [7]:
# save notebook as HTML ( the HTML will be saved in the same folder the original script is)
display(Javascript('IPython.notebook.save_checkpoint();'))
os.system(f'jupyter nbconvert --to html tools/preprocessing_tools/qc_reports/qc_report_funova_exp4.ipynb --output {NOVA_HOME}/manuscript/preprocessing_qc_reports/qc_report_funova_exp4_04.03.25.html')

[NbConvertApp] Converting notebook tools/preprocessing_tools/qc_reports/qc_report_funova_exp4.ipynb to html
[NbConvertApp] Writing 16644775 bytes to /home/labs/hornsteinlab/Collaboration/NOVA_GAL/NOVA/manuscript/preprocessing_qc_reports/qc_report_funova_exp4.html
Out[7]:
0
In [ ]: